Course Outline
What is AI and how it differs from other computer-based solutions?
AI value proposition
AI Types (Narrow vs Generic)
AI history and how it has evolved
AI trending applications and latest breakthrough
Deep-mind Applications.
Autonomous Vehicles.
Face recognition and Image interpretation.
NLP, chatbots, speech recognition, and translation.
Medical diagnosis and the impact on health sector.
AI in social media and marketing.
Data analysis AI applications.
Robotics and AI.
AI giving birth to a more intelligent AI systems.
Future applications.
How AI works? (Non technical overview)
Machine learning and pattern recognition.
Supervised, Unsupervised, and Reinforcement learning.
Neural Networks and Deep Learning.
Data analytics using AI, how it works.
How face recognition works?
Steps to train and test an AI model.
Leading AI Projects and Companies
General AI ( IBM Watson, Deep Mind, AYASDI).
Autonomous Driving Cars (Tesla, Waymo, Zoox..).
Speech recognition (Soundhound, Amazon Alexa,..).
News and data discovery (Dataminr).
Translation (Google).
Cybersecurity (Cylance).
Experiencing various AI applications (Hands-On)
Predicting Tomorrow’s Weather (Data analysis).
Quick Draw (Google AI lab).
AI generated Music Application.
AIUAE Strategy and Vision
Adopting AI roadmap
Setting up the problem – what is your AI goal?
What infrastructure will you need?
Start building your data.
Groups Brainstorming Activity: Participants to suggest solutions using AI to enhance their organization services
AI possible Risk and adoption implications
Effect of AI on jobs and employment. Which jobs will become obsolete.
Over trusting AI as decision maker.
How AI can evolve unpredictably and may become out of control.
Why AI and Blockchain can be a threat.